For categorical features, we do ordinary encoding to reduce memory usage.
For continuous features, we do standard scaling with mean and standard deviation.
Then we do quantile transformation for all features.
When fitting quantile transformation we add small gaussian nose.
Adding noise is crucial to have mean and standard deviation close to 0 and 1, respectively [1]}.
